China's main stock market index, the SHANGHAI, fell to 3560 points on August 1, 2025, losing 0.37% from the previous session. Over the past month, the index has climbed 3.04% and is up 22.53% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from China. China Shanghai Composite Stock Market Index - values, historical data, forecasts and news - updated on August of 2025.

According to a survey conducted by Ipsos on predictions for global issues in 2020, ** percent of Chinese believed it that major stock markets might crash in 2020. The results of the survey showed that Chinese were among the most optimistic regarding the stock market in 2020.

At the end of *************, the Shenzhen Component Index value was *********, an increase of about 1,000 index points from *************. The data clearly shows how the value of the index increased before the stock market crash of 2015 and the following sell-off in the following year. In addition to that, the low year-end index value of 2018 was the result of the worst trading year of the decade on Chinese stock exchanges. Together, stocks on the Shanghai and Shenzhen stock exchanges lost around ** percent in that year.

Hong Kong's main stock market index, the HK50, fell to 24508 points on August 1, 2025, losing 1.07% from the previous session. Over the past month, the index has climbed 1.18% and is up 44.63% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Hong Kong. Hong Kong Stock Market Index (HK50) - values, historical data, forecasts and news - updated on August of 2025.

Skechers' stock plummeted over 12% after the company released weaker-than-expected future projections, sparking concerns over its financial stability and exposure to potential US tariffs on Chinese goods.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Will the China A50 Index Continue Its Ascent?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Emotions are fundamental elements driving humans’ decision-making and information processing. Fear is one of the most common emotions influencing investors’ behaviors in the stock market. Although many studies have been conducted to explore the impacts of fear on investors’ investment performance and trading behaviors, little is known about factors contributing to and alleviating investors’ fear during the market crash (or extremely volatile periods) and their fear regulation after the crisis. Thus, the current data descriptor provides details of a dataset of 1526 Chinese and Vietnamese investors, a potential resource for researchers to fill in the gap. The dataset was designed and structured based on the information-processing perspective of the Mindsponge Theory and existing evidence in life sciences. The Bayesian Mindsponge Framework (BMF) analytics validated the data. Insights generated from the dataset are expected to help researchers expand the existing literature on behavioral finance and the psychology of fear, improve the investment effectiveness among investors, and inform policymakers on strategies to mitigate the negative impacts of market crashes on the stock market.

In 2021, the interest income from margin financing and securities lending business of CITIC Securities amounted to around *** billion yuan, ranking first among China's securities companies. After the stock market crash in 2015, China's securities market has been shrinking, demonstrating less trading revenue and lower profit rate. However, Chinese equity market has been gradually picking up since 2019.

Chinese listed companies data, encompasses stock price crash risk variables, audit system change records, and other necessary control variables. Date Submitted: 2023-11-18

China Shanghai-HK Stock Connect: Northbound Trading: HKEx: Daily Quota Balance data was reported at 53,786.230 RMB mn in 16 Aug 2024. This records an increase from the previous number of 42,370.380 RMB mn for 15 Aug 2024. China Shanghai-HK Stock Connect: Northbound Trading: HKEx: Daily Quota Balance data is updated daily, averaging 48,663.955 RMB mn from Nov 2014 (Median) to 16 Aug 2024, with 2264 observations. The data reached an all-time high of 63,559.880 RMB mn in 24 Oct 2022 and a record low of 0.000 RMB mn in 17 Nov 2014. China Shanghai-HK Stock Connect: Northbound Trading: HKEx: Daily Quota Balance data remains active status in CEIC and is reported by Hong Kong Exchanges and Clearing Limited (HKEx). The data is categorized under China Premium Database’s Financial Market – Table CN.ZA: Shanghai-Hong Kong SAR (China) Stock Connect: Quota and Usage Rate: Daily. Real-time available daily quota balance will be shown when it falls below 30%; otherwise indicated as “Available”. Real-time buy, sell and total turnover will not be available; historical daily/ monthly total market turnover, number of trades, ETF turnover, and turnover of the top 10 most actively traded stocks will be shown.

China Shanghai-HK Stock Connect: Northbound Trading: HKEx: Turnover Value: Buy data was reported at 22,080.140 RMB mn in 16 Aug 2024. This records a decrease from the previous number of 31,345.920 RMB mn for 15 Aug 2024. China Shanghai-HK Stock Connect: Northbound Trading: HKEx: Turnover Value: Buy data is updated daily, averaging 12,243.345 RMB mn from Nov 2014 (Median) to 16 Aug 2024, with 2264 observations. The data reached an all-time high of 51,967.530 RMB mn in 06 May 2024 and a record low of 344.160 RMB mn in 07 Jan 2016. China Shanghai-HK Stock Connect: Northbound Trading: HKEx: Turnover Value: Buy data remains active status in CEIC and is reported by Hong Kong Exchanges and Clearing Limited (HKEx). The data is categorized under China Premium Database’s Financial Market – Table CN.ZA: Shanghai-Hong Kong SAR (China) Stock Connect: Turnover Value and Number of Trades: Daily. Real-time available daily quota balance will be shown when it falls below 30%; otherwise indicated as “Available”. Real-time buy, sell and total turnover will not be available; historical daily/ monthly total market turnover, number of trades, ETF turnover, and turnover of the top 10 most actively traded stocks will be shown.

Key vaccine stocks like Moderna, Pfizer, and Novavax are rising as new coronavirus concerns emerge in China, highlighting a mixed day in the stock market with travel and tech sectors facing declines.

The USD/CNY exchange rate fell to 7.1922 on August 1, 2025, down 0.25% from the previous session. Over the past month, the Chinese Yuan has weakened 0.43%, and is down by 0.45% over the last 12 months. Chinese Yuan - values, historical data, forecasts and news - updated on August of 2025.

In 2021, China's securities company CITIC Securities generated over ** billion yuan in its operating income, ranking first among all securities companies in China. After the stock market crash in 2015, China's securities market has been shrinking, demonstrating less trading revenue and lower profit rate. However, Chinese equity market has been gradually picking up since 2019.

In 2025, stock markets in the United States accounted for roughly ** percent of world stocks. The next largest country by stock market share was China, followed by the European Union as a whole. The New York Stock Exchange (NYSE) and the NASDAQ are the largest stock exchange operators worldwide. What is a stock exchange? The first modern publicly traded company was the Dutch East Industry Company, which sold shares to the general public to fund expeditions to Asia. Since then, groups of companies have formed exchanges in which brokers and dealers can come together and make transactions in one space. Stock market indices group companies trading on a given exchange, giving an idea of how they evolve in real time. Appeal of stock ownership Over half of adults in the United States are investing money in the stock market. Stocks are an attractive investment because the possible return is higher than offered by other financial instruments.

Texas Instruments' stock fell 8.3% due to new Chinese regulations on chip imports, raising investor concerns amid U.S.-China trade tensions.

This study uses panel data on Chinese A-share listed companies in Shanghai and Shenzhen covering 2014 to 2020 selected through the following screening: first, we exclude listed companies in the finance and insurance sectors; second, we exclude listed companies in ST and *ST (Special Treatment); finally, we exclude samples that lack important data. This approach generates 8,658 valid research sample observations. The data are obtained from several official websites, such as those for CSMAR (China Stock Market & Accounting Research Database), CNRDS (Chinese Research Data Services), and the Shanghai and Shenzhen stock exchanges.In this study, the descriptive and relevance of the final data was tested using Stata software, and baseline regression, threshold regression, and robustness and heterogeneity tests were performed. The final data were tested for descriptiveness and correlation using Stata software, and baseline regression, threshold regression, and robustness and heterogeneity tests were performed.

Using the margin trading reform of China’s stock market as a quasinatural experiment, this paper explores whether margin trading promotes the high-quality development of listed companies. The results show that total factor productivity (TFP) significantly decreases after listed companies are included in the underlying stocks of margin trading. In addition, the negative impacts are stronger for listed companies with higher financial leverage, lower cash asset holdings, lower shareholdings of financial institution investors, and less attention from securities analysts. Further research shows that the negative impacts of margin trading on TFP are closely related to the deterioration of the information environment and the tightening of financing constraints. When listed companies are included in the underlying stocks of margin trading, they use a lower proportion of their net profit for internal financing (and a higher proportion of their net profit for cash dividends) and significantly reduce external equity financing. The results of this study show that the margin trading reform in China’s stock market may inhibit the high-quality development of listed companies to a certain extent.

Financial reporting quality is critical for businesses, stakeholders, and government to ensure transparency and accountability. The purpose of this paper is to investigate the relationship between corporate governance, financial reporting quality, and ownership structure as a moderating factor for Chinese stock exchange-listed firms. Quantitative data of 550 listed firms from 2012 to 2022 are collected from the annual reports. For investigating the relationship between variables, panel data analysis with random and fixed effect models is used. Our results show that corporate governance’s different attributes such as Auditor brand name, Existence of an audit committee, independent board, family ownership, and profitability have a significant negative impact on the audit report lag that decreases the lags and increases the financial reporting quality in China listed firms. Auditor opinion, Board diligence Board size, and CEO duality have a significant positive impact on the audit report lag that increases the lags and decreases the financial reporting quality of China-listed firms. Furthermore, our findings show that ownership concentration has no moderating effect between corporate governance, different attributes, and financial reporting quality. Family ownership, on the other hand, has a strong moderating effect between corporate governance characteristics and financial reporting quality. However, due to limitations, this study provides the opportunity for future research on corporate governance mechanisms in different cultures and environments. Moreover, this study has some important implications for investors, policymakers, and government.

China Shenzhen-HK Stock Connect: Northbound Trading: HKEx: Turnover Value: Buy data was reported at 20,561.170 RMB mn in 16 Aug 2024. This records a decrease from the previous number of 25,317.270 RMB mn for 15 Aug 2024. China Shenzhen-HK Stock Connect: Northbound Trading: HKEx: Turnover Value: Buy data is updated daily, averaging 22,538.290 RMB mn from Dec 2016 (Median) to 16 Aug 2024, with 1788 observations. The data reached an all-time high of 51,088.390 RMB mn in 07 Jul 2020 and a record low of 497.810 RMB mn in 29 Dec 2016. China Shenzhen-HK Stock Connect: Northbound Trading: HKEx: Turnover Value: Buy data remains active status in CEIC and is reported by Hong Kong Exchanges and Clearing Limited (HKEx). The data is categorized under China Premium Database’s Financial Market – Table CN.ZA: Shenzhen-Hong Kong SAR (China) Stock Connect: Turnover Value and Number of Trades: Daily. Real-time available daily quota balance will be shown when it falls below 30%; otherwise indicated as “Available”. Real-time buy, sell and total turnover will not be available; historical daily/ monthly total market turnover, number of trades, ETF turnover, and turnover of the top 10 most actively traded stocks will be shown.